Artificial intelligence-powered whole-slide image analyzer reveals a distinctive distribution of tumor-infiltrating lymphocytes in neuroendocrine tumors and carcinomas.
Authors: Hyung-Gyo Cho, Wonkyung Jung, Soo Ick Cho, Jiwon Shin, Gahee Park, Jimin Moon, Minuk Ma, Jeongun Ryu, Mohammad Mostafavi, Seonwook Park, Sergio Pereira, Kyunghyun Paeng, Donggeun Yoo, Chan-Young Ock, Seokhwi Kim
Journal: Journal of Clinical Oncology (2022)

e16214 Background: Immune checkpoint inhibitors (ICIs) have shown promising treatment outcomes for various types of tumors. However, in neuroendocrine tumors and carcinomas (NET/NEC), ICI has proven to be applicable for only limited cases. In addition, little is known about the immunoprofile of NET/NEC. Here we investigate the landscape of tumor-infiltrating lymphocytes (TIL) using artificial intelligence (AI)-powered H&amp;E whole-slide image (WSI) analyzer to elucidate the tumor microenvironment of NET/NEC. Methods: A total of 240 H&amp;E stained pathologic slides diagnosed with NET/NEC were obtained from Ajou University Medical Center in Korea (from January 2020 to December 2021). For spatial TIL analysis, we used Lunit SCOPE IO, an AI-powered H&amp;E WSI analyzer, which identifies and quantifies TIL within the cancer or stroma area. The AI was developed with a 13.5 x 10 9 μm 2 area and 6.2 x 10 6 TIL from 17,849 H&amp;E WSI of multiple cancer types, annotated by 104 board-certified pathologists. Intra-tumoral TIL, stromal TIL, and combined (cancer + stroma) TIL density were defined as the TIL count divided by the area of interest respectively. NET with histological grade 1 and 2 were labeled as low grade and NET with histological grade 3 and together with NEC were labeled as high grade. Primary origins of the NET/NEC were grouped by colorectum, stomach, small intestine, hepatopancreatobiliary, lung, and other organs (including anus, appendix, breast, cervix, and larynx). Results: Total slides classified as low grade and high grade were 211 and 29, respectively; 175 samples were from colorectal, 19 from stomach, 16 from small intestine, 16 from hepatopancreaticobiliary, seven from lung, and seven from other organs. The median intra-tumoral TIL, stromal TIL, and combined TIL density were 4.2/mm 2 (IQR 1.718 - 11.478), 139.1/mm 2 (IQR 75.4 - 313.9), and 62.4/mm 2 (IQR 36.3 - 162.6), respectively. The median intra-tumoral TIL density was significantly higher in patients with high grade NET/NEC compared with low grade (11.9/mm 2 [IQR 4.51 - 30.9] vs 3.45/mm 2 [IQR 1.63 - 9.81], p &lt; 0.001). However, statistical differences in stromal TIL density and combined TIL density were not observed between low grade and high grade NET/NEC. The highest intra-tumoral TIL density in the group classified according to primary origins was lung (n = 7, median: 16.5/mm 2 , IQR 5.01 - 34.1) and was followed by stomach (n = 19, median: 11.8/mm 2 , IQR 8.64 - 20.8), and small intestine (n = 16, median: 7.23/mm 2 , IQR 4.12 - 25.2). Conclusions: AI-powered TIL analysis reveals that the intra-tumoral TIL density is significantly higher in high grade NET/NEC than low grade NET. Our findings align with recent evidence that ICIs are effective against large cell NEC and small cell carcinoma.Therefore, AI-powered TIL analysis should be investigated as a predictive biomarker for ICI response in NET/NEC.